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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
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Characteristics of Marginalised Rural Areas in Europe and the Mediterranean Region: Shapeflie and associated attributes

Authors: Miller, David; McKeen, Margaret; Price, Martin; Slee, Bill; Nijnik, Maria;

Characteristics of Marginalised Rural Areas in Europe and the Mediterranean Region: Shapeflie and associated attributes

Abstract

The H2020 project on Social Innovation in Marginalised Rural Areas (SIMRA) focused on understanding social innovation and innovative governance in agriculture, forestry and rural development, and how to boost them, particularly in marginalised rural areas across Europe, with a focus on the Mediterranean region (including non-EU). Its geographic focus was on Marginalised Rural Areas (MRAs), which had not previously been defined. The analysis of the rural areas of Europe and the Mediterranean area required data of consistent spatial and temporal resolutions for variables of three types: physical geography, infrastructure (spatial marginality), and socio-economic (societal marginality). There few datasets of relevance that exist for the entire area, creating a need to derive spatial datasets and produce associated maps of the characteristics that contribute to marginality or marginalization. The outputs comprise new spatial datasets at resolutions compatible with the underlying information (e.g. 1km2, NUTS 3, NUTS 2, and local authorities in North Africa and the eastern Mediterranean), enabling comparisons between such areas. The associated maps and a tabulation of the characteristics for the entire area of interest to SIMRA are reported in Price et al. (2017). This spatial dataset contains the characteristics of the Marginalised Rural Areas as attributes in a Shapefle for use in a Geographic Information System. Details of the attributes in the Shapefle, and their values, are provided in the MS Excel spreadsheet downloadable with this dataset. Reference: Price, M., Miller, D.R., McKeen, M., Slee, W. and Nijnik, M. 2017. Categorisation of marginalised rural areas (MRAs). Deliverable 3.1, Social Innovation in Marginalised Rural Areas (SIMRA). Report to the European Commission, pp. 57. 10.5281/zenodo.3625493 The boundaries in the spatial dataset are complied from: Nomenclature of Territorial Units for Statistics (NUTS) 2013 European Commission, © EuroGeographics, © FAO (UN), © TurkStat Source: European Commission – Eurostat/GISCO© for administrative boundaries. All other boundary data were extracted from the GADM database (www.gadm.org), version 2.8, November 2015. They can be used for non-commercial purposes only. It is not allowed to redistribute these data, or use them for commercial purposes, without prior consent. See the website for more information.

The spatial dataset of characteristics of Marginalised Rural Areas is explained in Price et al., 2017 (10.5281/zenodo.3625493). Suggested citation: Miller, D.R., McKeen, M., Price, M., Slee, W. and Nijnik, M. 2020. Characteristics of marginalised rural areas (MRAs). Spatial dataset with attributes containing the table of characteristics. Social Innovation in Marginalised Rural Areas (SIMRA). James Hutton Institute, UK.

{"references": ["Suggested citation: Price, M., Miller, D.R., McKeen, M., Slee, W. and Nijnik, M. 2017. Categorisation of marginalised rural areas (MRAs). Deliverable 3.1, Social Innovation in Marginalised Rural Areas (SIMRA). Report to the European Commission, pp. 57."]}

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Keywords

Europe, Middle East, Characteristics, NUTS 3, Geographic Information Systems, Social Innovation, Marginalised Rural Areas (MRAs), North Africa, Shapefile, Table of Areas

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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